In recent years, the motion capture technologies have been widely applied in the capture and analysis of players' motions in sports. Typically, a motion capture technology can digitally record the motions of an object. Currently, the motion capture technologies that are commonly employed include an optics-based motion capture technology and an inertial sensor-based motion capture technology.
An optics-based motion capture technology typically includes a plurality of cameras, which are arranged around an object under measurement, and the object is further configured to have a range of movement in an overlapped area of the perspectives of the plurality of cameras. Typically, a plurality of special reflective points or luminous points (i.e. optical markers) are attached onto some key parts of the object to thereby serve as markers allowing for visual identification and data processing.
After calibration, each camera is configured to continuously photograph the motions of the object and to record image sequences for further analysis and processing. Based on the image sequences, a spatial position of each optical marker at each moment can be calculated, thereby allowing for an accurate determination of the motion tracks of the object.
The optics-based motion capture technology involves no mechanical devices or cables, and are thus free from their restrictions, which allows the object to have a relatively larger range of movement, and further allows a relatively higher sampling frequency. However, by means of the above optics-based motion capture technology, the motion of the object can be captured only when the object's motion is within the overlapped area of the cameras' perspectives. In addition, when the motion of the object is complex, the optical markers can be easily blocked and cause confusions, resulting in erroneous results.
Conventionally, mechanical inertial sensors have long been employed in the navigation of aircrafts and ships. With the rapid development of microelectromechanical systems (MEMS), the micro inertial sensor technology has become relatively mature, and in recent years, people have attempted to employ the MEMS inertial sensor technology in motion captures.
One basic approach is to couple or attach an inertial measurement unit (IMU) onto an object to be measured, which thus moves along with the object. The inertial measurement unit usually includes a MEMS accelerometer and a MEMS gyroscope, which are configured to measure an acceleration signal and an angular velocity signal (i.e. a gyro signal) respectively. Based on a double integration of the acceleration signal and an integration of the gyro signal, the position information and the orientation information of the object can be obtained.
Due to the application of MEMS technology, the IMU can have a small size and a light weight, thus having little influence on the movement of the object to be measured. In addition, the MEMS-based IMU has a low requirement for the activity field, and is typically not affected by lights and shades (or blocks), thus allowing for a relatively large range of movement for the object. Nonetheless, the integration drift that is intrinsically associated with the inertia-based motion capture technology has resulted in a relatively low motion capture accuracy.
U.S. Pat. No. 8,203,487 discloses a motion capture system and method that combines ultra-wideband (UWB) measurements and MEMS-based inertial measurements. According to the disclosure, the motion capture system includes: 1) a sensor unit, comprising a plurality of UWB transmitters and a plurality of inertial measurement sensors; 2) a plurality of UWB receivers, configured to receive, remotely from the object, data from each of the plurality of UWB transmitters to thereby obtain the time of arrival (TOA) of each inertial measurement sensor, wherein the plurality of UWB transmitter and the plurality of inertial measurement sensors are synchronized at the hardware level; and 3) a processor, configured to receive the TOA data and the inertial data, and to integrate the TOA data and the inertial data to obtain the position and orientation of an object to be measured.
In this above motion capture system that combines the use of UWB and inertial measurement sensors, primarily due to a relatively poor positioning accuracy of UWB, even though the combination of inertial measurement sensors and the employment of certain arithmetic processing allows the motion trajectory captured to be relatively smooth, they cause limited improvement to the positioning accuracy.
In addition, a UWB device can only be employed in positioning on a horizontal plane, and cannot be used for positioning in the vertical direction. Although the aforementioned motion capture system further includes a pressure sensor (barometer) in an attempt to solve the issue, the pressure sensor itself has a relatively low positioning accuracy.
Furthermore, the motion capture system as described above requires a plurality of UWB receivers. Thus in cases where the scene for motion capture needs to be changed, a relatively longer time is needed to set up and calibrate the various devices in the system.
U.S. patent application (Pub No. US20130028469A1) substantially discloses the combination of optical markers with inertial sensors for capturing the position and orientation of an object. A marker determining unit is utilized to determine a position of a marker in a two-dimensional (2D) image. A depth determining unit is utilized to determine, in a depth image, a position corresponding to the position of the marker in the 2D image, and to determine a depth of the corresponding position in the depth image to be a depth of the marker. A marker-based estimator is utilized to estimate, based on the depth of the marker, a marker-based position indicating a three-dimensional (3D) position of the marker.
At the same time, an inertial sensor unit is further utilized to obtain an inertia-based position and an inertia-based orientation. Ultimately a fusion estimator can be used to estimate a fused position and an inertia-based orientation, based on a weighted-sum of the marker-based position and the inertia-based position, where the weighted-sum is calculated based on a movement speed and a position of the object, the inertia-based position, and the inertia-based orientation.
The motion capture technology as described above is only able to capture the motion of a single node, but is unable to capture the complex motions of an object having multiple nodes or joints.